Triple
T1657140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicklas Bäckström |
E35824
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Nicklas
Nicklas is a masculine given name of Scandinavian origin, commonly used in Sweden and other Nordic countries.
|
E187829
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Nicklas | Statement: [Nicklas Bäckström, givenName, Nicklas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicklas Context triple: [Nicklas Bäckström, givenName, Nicklas]
-
A.
Nick
Nick is the given name of Nick Holonyak Jr., the American engineer and inventor widely known for creating the first practical visible-spectrum LED.
-
B.
Jonas Wendell
Jonas Wendell was a 19th-century American Adventist preacher whose prophetic teachings on Christ’s return significantly shaped early Bible Student thought.
-
C.
Niels
Niels is the given name of the pioneering Norwegian mathematician Niels Henrik Abel, known for his foundational work in algebra and analysis.
-
D.
Jens
Jens is a masculine given name commonly used in Scandinavian and German-speaking countries, equivalent to "John" in English.
-
E.
Nik
Nik is one of the three futuristic, anime-style "Spheriks" characters that served as official mascots for the 2002 FIFA World Cup in South Korea and Japan.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nicklas Triple: [Nicklas Bäckström, givenName, Nicklas]
Generated description
Nicklas is a masculine given name of Scandinavian origin, commonly used in Sweden and other Nordic countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nicklas Target entity description: Nicklas is a masculine given name of Scandinavian origin, commonly used in Sweden and other Nordic countries.
-
A.
Nick
Nick is the given name of Nick Holonyak Jr., the American engineer and inventor widely known for creating the first practical visible-spectrum LED.
-
B.
Jonas Wendell
Jonas Wendell was a 19th-century American Adventist preacher whose prophetic teachings on Christ’s return significantly shaped early Bible Student thought.
-
C.
Niels
Niels is the given name of the pioneering Norwegian mathematician Niels Henrik Abel, known for his foundational work in algebra and analysis.
-
D.
Jens
Jens is a masculine given name commonly used in Scandinavian and German-speaking countries, equivalent to "John" in English.
-
E.
Nik
Nik is one of the three futuristic, anime-style "Spheriks" characters that served as official mascots for the 2002 FIFA World Cup in South Korea and Japan.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a88606aa808190aa0b421b4271f220 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a8d85f08190a50ade3f443b7703 |
completed | March 5, 2026, 4:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad68254a6081909c2222fd77dff648 |
completed | March 8, 2026, 12:14 p.m. |
| NEDg | Description generation | batch_69ad68a9769081908a0748b8d02b8379 |
completed | March 8, 2026, 12:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad692d61288190ad0c0265f49643ac |
completed | March 8, 2026, 12:18 p.m. |
Created at: March 4, 2026, 7:29 p.m.